Towards {TerraSAR}-{X} {Street} {View}: {Creating} {City} {Point} {Cloud} from {Multi}-{Aspect} {Data} {Stacks}

This article presents a recent updates of urban monitoring using TerraSAR-X data. We demonstrate a Google Street-View-like point cloud of the city of Berlin. To make such a point cloud, synthetic aperture radar (SAR) tomography is employed to process TerraSAR-X data stacks of different view angles around Berlin, obtaining 3D point cloud subsets from each of these data stacks. The density of one of these point clouds is around 1 million points / km2. These point cloud subsets are then fused to create a complete seamless one. Fuse tens of millions of points is a challenging task. Therefore, in this article, particular focus is put on the point cloud fusion. We introduce a feature-based unsupervised technique for point clouds fusion by detecting and matching building contour end points and aligning flat roofs in the two point clouds. The same idea can also be exploited as a general way to evaluate the fusion accuracy of different fusion techniques.     «

This article presents a recent updates of urban monitoring using TerraSAR-X data. We demonstrate a Google Street-View-like point cloud of the city of Berlin. To make such a point cloud, synthetic aperture radar (SAR) tomography is employed to process TerraSAR-X data stacks of different view angles around Berlin, obtaining 3D point cloud subsets from each of these data stacks. The density of one of these point clouds is around 1 million points / km2. These point cloud subsets are then fused to cr...     »